Semantic Segmentation of Remote Sensing Data Based on Channel Attention and Feature Information Entropy.

The common channel attention mechanism maps feature statistics to feature weights. However, the effectiveness of this mechanism may not be assured in remotely sensing images due to statistical differences across multiple bands. This paper proposes a novel channel attention mechanism based on feature information called the feature information entropy attention mechanism (FEM). The FEM constructs a relationship between features based on feature information entropy and then maps this relationship to their importance. The Vaihingen dataset and OpenEarthMap dataset are selected for experiments. The proposed method was compared with the squeeze-and-excitation mechanism (SEM), the convolutional block attention mechanism (CBAM), and the frequency channel attention mechanism (FCA). Compared with these three channel attention mechanisms, the mIoU of the FEM in the Vaihingen dataset is improved by 0.90%, 1.10%, and 0.40%, and in the OpenEarthMap dataset, it is improved by 2.30%, 2.20%, and 2.10%, respectively. The proposed channel attention mechanism in this paper shows better performance in remote sensing land use classification.

Evaluation of Several Satellite-Based Soil Moisture Products in the Continental US.

Satellite-based soil moisture products are suitable for large-scale regional monitoring due to the accessibility. Five soil moisture products including SMAP, ESA CCI, and AMSR2 (ascending, descending, and average) were selected in the continental United States (US) from 2016 to 2021. To evaluate the performance of the products and assess their applicability, ISMN (International Soil Moisture Network) data were used as the in situ measurement. PBIAS (Percentage of BIAS), R (Pearson correlation coefficient), RMSE (Root Mean Square Error), ubRMSE (unbiased RMSE), MAE (Mean Absolute Error), and MBE (Mean Bias Error) were selected for evaluation. The performance of five products over six observation networks and various land cover types was compared, and the differences were analyzed at monthly, seasonal, and annual scales. The results show that SMAP had the smallest deviation with the ISMN data because PBIAS was around -0.13, and MBE was around -0.02 m3/m3. ESA CCI performed the best in almost all aspects; its R reached around 0.7, and RMSE was only around 0.07 m3/m3 at the three time scales. The performance of the AMSR2 products varied greatly across the time scales, and increasing errors and deviations showed from 2016 to 2020. The PBO_H2O and USCRN networks could reflect soil moisture characteristics in the continental US, while iRON performed poorly. The evaluation of the networks was closely related to spatial distributions. All products performed better over grasslands and shrublands with R, which was greater than 0.52, and ubRMSE was around 0.1 m3/m3, while products performed worse over forests, where PBIAS was less than -0.62, and RMSE was greater than 0.2 m3/m3, except for ESA CCI. From the boxplot, SMAP was close to the ISMN data with differences less than 0.004 m3/m3 between the median and lower quartiles.

Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010.

Drought is a type of natural disaster that has the most significant impacts on agriculture. Regional drought monitoring based on remote sensing has become popular due to the development of remote sensing technology. In this study, vegetation condition index (VCI) data recorded from 1982 to 2010 in agricultural areas of China were obtained from advanced very high resolution radiometer (AVHRR) data, and the temporal and spatial variations in each drought were analyzed. The relationships between drought and climate factors were also analyzed. The results showed that from 1982 to 2010, the agricultural areas that experienced frequent and severe droughts were mainly concentrated in the northwestern areas and Huang-Huai Plain. Moreover, the VCI increased in the majority of agricultural areas, indicating that the drought frequency decreased over time, and the decreasing trend in the southern region was more notable than that in the northern region. A correlation analysis showed that temperature and wind velocity were the main factors that influenced drought in the agricultural areas of China. From a regional perspective, excluding precipitation, the climate factors had various effects on drought in different regions. However, the correlation between the VCI and precipitation was low, possibly due to the widespread use of artificial irrigation technology, which reduces the reliance of agricultural areas on precipitation.

An efficient approach for pixel decomposition to increase the spatial resolution of land surface temperature images from MODIS thermal infrared band data.

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250-500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world.

Related factors based on non-targeted metabolomics methods in minor ischaemic stroke.

Objective: This study aimed to identify potential biomarkers associated with the occurrence of minor ischaemic stroke. Methods: Four hundred patients hospitalized with minor ischaemic stroke were enrolled in the department of neurological internal medicine in Taiyuan Central Hospital, and 210 healthy subjects examined at the Taiyuan Central Hospital Medical Center during the same period were selected. We collected information on the general demographic characteristics and fasting blood samples of the subjects. We then used untargeted metabolomic assay to measure blood glucose, blood lipids, homocysteine, and high-sensitivity C-reactive protein. Results: There were statistically significant differences between the mild ischemic stroke group and the healthy control group in smoking, hypertension, and physical activity (P< 0.05). Compared with the healthy group, the minor ischaemic stroke group showed increased lactate, pyruvate, trimetlylamine oxide levels, and lactic acid, pyruvic acid, and trimethylamine N-oxidation (TMAO) levels were statistically significant (P< 0.001). In the minor ischaemic stroke risk model, hypertension, physical activity, smoking, and elevated TMAO levels influenced the occurrence of minor stroke. Conclusion: Increased levels of lactic acid, pyruvate, and TMAO may be related to the pathophysiological changes in the minor ischaemic stroke population. High blood pressure, a lack of physical activity, smoking, and increased TMAO level were the influencing factors for the occurrence of minor ischaemic stroke. The serum metabolite TMAO may be associated with MS occurrence.

Spatial-Temporal Variation of Drought in China from 1982 to 2010 Based on a modified Temperature Vegetation Drought Index (mTVDI).

Droughts cause huge losses of society and environment, therefore it is important to study the spatial-temporal pattern of drought. The traditional remote sensing drought indices (AVI, VCI and TCI) only consider the single factor representing the soil moisture (surface temperature or NDVI). The comprehensive remote sensing drought indices (VSWI and TVDI) can estimate the soil moisture more accurately, but they are not suitable for large scale region especially with great elevation variation. In this study, a modified Temperature Vegetation Drought Index (mTVDI) was constructed based on the correction of elevation and dry edge. Compared with the traditional drought indices, mTVDI had a better relationship with soil moisture in all selected months (R = -0.376, -0.406, -0.459, and -0.265, p < 0.05). mTVDI was used to analyze the spatial-temporal patterns of drought in China from 1982 to 2010. The results showed that droughts appeared more frequently in Northwest China and the southwest of Tibet while drought centers of North and Southwest China appeared in Huanghuaihai Plain and Yunnan-Guizhou Plateau respectively. The frequency of drought was increasing as a whole while the frequency of severe drought increased significantly by 4.86% and slight drought increased slowly during 1982 to 2010. The results are useful for the understanding of drought and policy making of climate change.